Crop Classification using Biologically-inspired Techniques with High Resolution Satellite Image

Remote sensing provides a lucid and effective means for crop coverage identification. Crop coverage identification is a very important technique, as it provides vital information on the type and extent of crop cultivated in a particular area. This information has immense potential in the planning for further cultivation activities and for optimal usage of the available fertile land. As the frontiers of space technology advance, the knowledge derived from the satellite data has also grown in sophistication. Further, image classification forms the core of the solution to the crop coverage identification problem. No single classifier can prove to satisfactorily classify all the basic crop cover mapping problems of a cultivated region. We present in this paper the experimental results of multiple classification techniques for the problem of crop cover mapping of a cultivated region. A detailed comparison of the algorithms inspired by social behaviour of insects and conventional statistical method for crop classification is presented in this paper. These include the Maximum Likelihood Classifier (MLC), Particle Swarm Optimisation (PSO) and Ant Colony Optimisation (ACO) techniques. The high resolution satellite image has been used for the experiments.

Parallel processor scheduling for minimizing total weighted tardiness using ant colony optimization

In the modern business environment, meeting due dates and avoiding delay penalties are very important goals that can be accomplished by minimizing total weighted tardiness. We consider a scheduling problem in a system of parallel processors with the objective of minimizing total weighted tardiness. Our aim in the present work is to develop an efficient algorithm for solving the parallel processor problem as compared to the available heuristics in the literature and we propose the ant colony optimization approach for this problem. An extensive experimentation is conducted to evaluate the performance of the ACO approach on different problem sizes with the varied tardiness factors. Our experimentation shows that the proposed ant colony optimization algorithm is giving promising results compared to the best of the available heuristics.

Urban satellite image classification using biologically inspired techniques

This paper focuses on optimisation algorithms inspired by swarm intelligence for satellite image classification from high resolution satellite multi- spectral images. Amongst the multiple benefits and uses of remote sensing, one of the most important has been its use in solving the problem of land cover mapping. As the frontiers of space technology advance, the knowledge derived from the satellite data has also grown in sophistication. Image classification forms the core of the solution to the land cover mapping problem. No single classifier can prove to satisfactorily classify all the basic land cover classes of an urban region. In both supervised and unsupervised classification methods, the evolutionary algorithms are not exploited to their full potential. This work tackles the land map covering by Ant Colony Optimisation (ACO) and Particle Swarm Optimisation (PSO) which are arguably the most popular algorithms in this category. We present the results of classification techniques using swarm intelligence for the problem of land cover mapping for an urban region. The high resolution Quick-bird data has been used for the experiments.

Detection of multiple source locations using a glowworm metaphor with applications to collective robotics

This paper presents a glowworm swarm based algorithm that finds solutions to optimization of multiple optima continuous functions. The algorithm is a variant of a well known ant-colony optimization (ACO) technique, but with several significant modifications. Similar to how each moving region in the ACO technique is associated with a pheromone value, the agents in our algorithm carry a luminescence quantity along with them. Agents are thought of as glowworms that emit a light whose intensity is proportional to the associated luminescence and have a circular sensor range. The glowworms depend on a local-decision domain to compute their movements. Simulations demonstrate the efficacy of the proposed glowworm based algorithm in capturing multiple optima of a multimodal function. The above optimization scenario solves problems where a collection of autonomous robots is used to form a mobile sensor network. In particular, we address the problem of detecting multiple sources of a general nutrient profile that is distributed spatially on a two dimensional workspace using multiple robots.

Scheduling parallel batch processors with incompatible job families using ant colony optimization

The present work concerns with the static scheduling of jobs to parallel identical batch processors with incompatible job families for minimizing the total weighted tardiness. This scheduling problem is applicable in burn-in operations and wafer fabrication in semiconductor manufacturing. We decompose the problem into two stages: batch formation and batch scheduling, as in the literature. The Ant Colony Optimization (ACO) based algorithm called ATC-BACO algorithm is developed in which ACO is used to solve the batch scheduling problems. Our computational experimentation shows that the proposed ATC-BACO algorithm performs better than the available best traditional dispatching rule called ATC-BATC rule.

Tool wear monitoring using ant behaviour

In this paper we show the applicability of Ant Colony Optimisation (ACO) techniques for pattern classification problem that arises in tool wear monitoring. In an earlier study, artificial neural networks and genetic programming have been successfully applied to tool wear monitoring problem. ACO is a recent addition to evolutionary computation technique that has gained attention for its ability to extract the underlying data relationships and express them in form of simple rules. Rules are extracted for data classification using training set of data points. These rules are then applied to set of data in the testing/validation set to obtain the classification accuracy. A major attraction in ACO based classification is the possibility of obtaining an expert system like rules that can be directly applied subsequently by the user in his/her application. The classification accuracy obtained in ACO based approach is as good as obtained in other biologically inspired techniques.

Glowworm-inspired robot swarm for simultaneous taxis towards multiple radiation sources

This paper presents a glowworm metaphor based distributed algorithm that enables a collection of minimalist mobile robots to split into subgroups, exhibit simultaneous taxis-behavior towards, and rendezvous at multiple radiation sources such as nuclear/hazardous chemical spills and fire-origins in a fire calamity. The algorithm is based on a glowworm swarm optimization (GSO) technique that finds multiple optima of multimodal functions. The algorithm is in the same spirit as the ant-colony optimization (ACO) algorithms, but with several significant differences. The agents in the glowworm algorithm carry a luminescence quantity called luciferin along with them. Agents are thought of as glowworms that emit a light whose intensity is proportional to the associated luciferin. The key feature that is responsible for the working of the algorithm is the use of an adaptive local-decision domain, which we use effectively to detect the multiple source locations of interest. The glowworms have a finite sensor range which defines a hard limit on the local-decision domain used to compute their movements. Extensive simulations validate the feasibility of applying the glowworm algorithm to the problem of multiple source localization. We build four wheeled robots called glowworms to conduct our experiments. We use a preliminary experiment to demonstrate the basic behavioral primitives that enable each glowworm to exhibit taxis behavior towards source locations and later demonstrate a sound localization task using a set of four glowworms.

Generating artificial chromosomes with probability control in genetic algorithm for machine scheduling problems

In this paper, a novel genetic algorithm is developed by generating artificial chromosomes with probability control to solve the machine scheduling problems. Generating artificial chromosomes for Genetic Algorithm (ACGA) is closely related to Evolutionary Algorithms Based on Probabilistic Models (EAPM). The artificial chromosomes are generated by a probability model that extracts the gene information from current population. ACGA is considered as a hybrid algorithm because both the conventional genetic operators and a probability model are integrated. The ACGA proposed in this paper, further employs the ``evaporation concept'' applied in Ant Colony Optimization (ACO) to solve the permutation flowshop problem. The ``evaporation concept'' is used to reduce the effect of past experience and to explore new alternative solutions. In this paper, we propose three different methods for the probability of evaporation. This probability of evaporation is applied as soon as a job is assigned to a position in the permutation flowshop problem. Experimental results show that our ACGA with the evaporation concept gives better performance than some algorithms in the literature.

DNA-binding and nuclease activity of1,10-phenanthroline-based thiocyanato, acetato, azido and benzoato bridged dinuclear copper(II) complexes

The mononuclear Cu(II) complex [Cu(phen)(H2O)(NO3)(2)] (1), obtained by the reaction of 1,10-phenanthroline with Cu(NO3)(2)center dot 3H(2)O in methanol solution, reacts with anionic ligands SCN-, AcO-, N-3(-) and PhCO2- in MeOH solution to form the stable binuclear complexes [Cu-2(H2O)(2)(phen)(2)(mu-X)(2)](2) (NO3)(2), where X = SCN- (2), AcO- (3), N-3(-) (4) or PhCO2- (5). The molecular structure of complex 3 was determined by single-crystal X-ray diffraction studies. These complexes were characterized by electronic, IR, ESR, magnetic moments and conductivity measurements. The electrochemical behaviour of the complexes was investigated by cyclic voltammetry. The interactions of these complexes with calf thymus DNA have been investigated using absorption spectrophotometry. Their DNA cleavage activity was studied on double-stranded pBR322 plasmid DNA using gel electrophoresis experiments in the absence and presence of H2O2 as oxidant.

DNA-binding and nuclease activity of 1,10-phenanthroline-based thiocyanato, acetato, azido and benzoato bridged dinuclear copper(II) complexes

The mononuclear Cu(II) complex [Cu(phen)(H2O)(NO3)(2)] (1), obtained by the reaction of 1,10-phenanthroline with Cu(NO3)(2)center dot 3H(2)O in methanol solution, reacts with anionic ligands SCN-, AcO-, N-3(-) and PhCO2- in MeOH solution to form the stable binuclear complexes [Cu-2(H2O)(2)(phen)(2)(mu-X)(2)](2) (NO3)(2), where X = SCN- (2), AcO- (3), N-3(-) (4) or PhCO2- (5). The molecular structure of complex 3 was determined by single-crystal X-ray diffraction studies. These complexes were characterized by electronic, IR, ESR, magnetic moments and conductivity measurements. The electrochemical behaviour of the complexes was investigated by cyclic voltammetry. The interactions of these complexes with calf thymus DNA have been investigated using absorption spectrophotometry. Their DNA cleavage activity was studied on double-stranded pBR322 plasmid DNA using gel electrophoresis experiments in the absence and presence of H2O2 as oxidant.

Dual Role of Acetate as a Nucleophile and as an Internal Base in Cycloplatination Reaction of sym-N,N `,N `'-Triarylguanidines

Reaction of cis-Cl2Pt(S(O)Me-2)(2)] with 1 equiv of sym-N,N',N `'-triarylguanidines, ArN=C(NHAr)(2) (sym = symmetrical; Ar = 2-MeC6H4 (LH22-tolyl), 2-(MeO)C6H4 (LH22-anisyl), 4-MeC6H4 (LH24-tolyl), 2,5-Me2C6H3 (LH22,5-xylyl), and 2,6-Me2C6H3 (LH22,6-xylyl)) in toluene under reflux condition for 3 h afforded cis- or trans-Cl2Pt(S(O)Me-2)(ArN=C(NHAr)(2))] (Ar = 2-MeC6H4 (1), 2-(MeO)C6H4 (2), 4-MeC6H4 (3), 2,5-h Me2C6H3 (4), and 2,6-Me2C6H3 (5), respectively) in 83-96% yield. Reaction of cis-Cl2Pt(S(O)Me-2)(2)] with 1 equiv of LH22-tolyl and LH24-tolyl in the presence of 1 equiv of NaOAc in methanol under reflux condition for 3 h afforded acetate-substituted products, cis-(AcO)ClPt(S(O)Me-2)(ArN=C(NHAr)(2))] (Ar = 2-MeC6H4 (6) and 4-MeC6H4 (7)) in 83% and 84% yields, respectively. Reaction of cis-Cl2Pt(S(O)Me-2)(2)] with 1 equiv of LH22-anisyl and LH22-tolyl in the presence of 1 equiv of NaOAc in methanol under reflux condition for 3 and 12 h afforded six-membered C,N] platinacycles, Pt{kappa(2)(C,N)-C6H3R-3(NHC(NHAr)(=NAr))-2}Cl(S(O)Me-2)] (Ar = 2-RC6H4; R = OMe (8) and Me (9)), in 92% and 79% yields, respectively. The new complexes have been characterized by analytical and spectroscopic techniques, and further the molecular structures of 1, 2, 4, 5, 6, and 8 have been determined by single-crystal X-ray diffraction. The platinum atom in 1, 4, and 5 exhibited the trans configuration, while that in 2, 6, and 8 exhibited the cis configuration. Complex 6 is shown to be the precursor for 9, and the former is suggested to transform to the latter possibly via an intramolecular C-H activation followed by elimination of AcOH. The solution behavior of new complexes has been studied by multinuclear NMR (H-1, Pt-195, and C-13) spectroscopy. The new complexes exist exclusively as a single isomer (trans (1 and 5) and cis (6 and 7)), a mixture of cis and trans isomers with the former isomer being predominant in the case of 2 and the latter isomer being predominant in the case of 3. Complex 5 in the trans form revealed the presence of one isomer at 0.007 mM concentration and two isomers in about 1.00:0.12 ratio at 0.154 mM concentration as revealed by H-1 NMR spectroscopy, and this has been ascribed to the restricted Pt-S bond rotation at higher concentration. Platinacycle 8 exists as one isomer, while 9 exists as a mixture of seven isomers in solution. The influence of steric factor, pi-acceptor property of the guanidine, subtle solid-state packing forces upon the configuration of the platinum atom, and the number of isomers in solution have been outlined. Factors that accelerate or slow down the cycloplatination reaction, the role of NaOAc, and a plausible mechanism of this reaction have been discussed.

Substituent effect on fluorescence signaling of the cell permeable HSO4- receptors through single point to ratiometric response in green solvent

Two new 2-(2-aminophenyl)benzimidazole-based HSO4- ion selective receptors, 6-(4-nitrophenyl)-5,6-dihydrobenzo4,5]imidazo1,2-c]quinazoline (L1H) and 6-(4-methoxyphenyl)-5,6-dihydrobenzo4,5]imidazo1,2-c] quinazoline (L2H), and their 1 : 1 molecular complexes with HSO4- were prepared in a facile synthetic method and characterized by physicochemical and spectroscopic techniques along with the detailed structural analysis of L1H by single crystal X-ray crystallography. Both receptors (L1H and L2H) behave as highly selective chemosensor for HSO4- ions at biological pH in ethanol-water HEPES buffer (1/5) (v/v) medium over other anions such as F-, Cl-, Br-, I-, AcO-, H2PO4-, N-3(-) and ClO4-. Theoretical and experimental studies showed that the emission efficiency of the receptors (L1H and L2H) was tuned successfully through single point to ratiometric detection by employing the substituent effects. Using 3 sigma method the LOD for HSO4- ions were found to be 18.08 nM and 14.11 nM for L1H and L2H, respectively, within a very short responsive time (15-20 s) in 100 mM HEPES buffer (ethanol-water: 1/5, v/v). Comparison of the utility of the probes (L1H and L2H) as biomarkers for the detection of intracellular HSO4- ions concentrations under a fluorescence microscope has also been included and both probes showed no cytotoxic effect.